Strong convergence for weighted sums of (α, β)-mixing random variables and application to simple linear EV regression model

被引：0

作者：

Hu, Wenjing ^{[1
]}

Wang, Wei ^{[1
]}

Wu, Yi ^{[1
]}

机构：

[1] Chizhou Univ, Ctr Appl Math, Sch Big Data & Artificial Intelligence, Chizhou 247000, Peoples R China

来源：

OPEN MATHEMATICS | 2024年 / 22卷 / 01期

关键词：

(alpha; beta)-mixing random variables; complete convergence; strong law of large numbers; simple linear errors-in-variables model; ASYMPTOTIC PROPERTIES; MOMENT CONVERGENCE; LS ESTIMATORS; CONSISTENCY;

D O I：

10.1515/math-2024-0003

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

In this article, the complete convergence and the Kolmogorov strong law of large numbers for weighted sums of (alpha, beta)-mixing random variables are presented. An application to simple linear errors-in-variables model is provided. Simulation studies are also carried out to support the theoretical results.

引用

页数：15

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